AI Space Solutions Developer

We reimagine how satellites process and deliver intelligence from space.

Our team specializes in satellite edge computing, developing advanced solutions that process data directly on board. This enables real-time analysis, rapid decision-making, and a significant reduction in data downlink needs.

This capability unlocks critical advantages across defense, environmental monitoring, and global communications. It provides insights with speed, efficiency, and security right from orbit.

We are based globally and work on solving complex challenges in earth observation, space situational awareness, and autonomous satellite operations.

The position is available for candidates based in specific locations only.

As the Data Scientist and reporting to the Head of Data Science, you will be part of the development team exploring different use cases for the technology, and working closely with the CTO to strategize the product and company's roadmap.

Leveraging sophisticated modeling techniques, we build the future of Space Edge Computing. The role requires excellent communication skills to coordinate with global teams and external partners.

• You will proactively use modern AI tools to enhance productivity across the data science lifecycle.
• Designing and implementing state-of-the-art computer vision and ML models for satellite imagery.
• Training and fine-tuning deep learning models for edge deployment, balancing performance with efficiency, power, and computational constraints.
• Providing MLOps, orchestration, and workflow best practices.
• Cross-functional collaboration with GIS engineers, software teams, and product managers to integrate ML solutions into our pipeline.
• Innovation & Research: staying ahead of emerging trends in Edge AI, ML, and remote sensing.
• Data handling: processing large, complex datasets from diverse sensors.
• Communication & Reporting: clearly articulating technical concepts, results, and trade-offs to both technical and non-technical stakeholders.
• Quality & Validation: ensuring robustness, reliability, and reproducibility of solutions through systematic testing, benchmarking, and validation.

Success metrics include delivering machine learning modules on schedule for satellite missions or user trials, deploying products for multiple satellite missions, demonstrated productivity gains, effective collaboration and communication across distributed teams, and contributions shaping the product roadmap.

To succeed in this role, you will need:

• Bachelor's or Master's in Computer Science, Data Science, Artificial Intelligence, or a related field.
• 3–8 years in data science, with demonstrated hands-on experience in computer vision, image processing, or machine learning.
• Technical Skills:

Strong in Python; experience with frameworks like TensorFlow, PyTorch, OpenCV.

General Software engineering: cloud infrastructure, Docker, git best practices.

Exposure to C/C++, CUDA, ONNX, TensorRT, OpenVINO, or FPGA acceleration is a plus.

Experience with architectures such as CNNs, ViTs, GANs and foundational models etc

Experience with model compression is a plus.

Familiarity with satellite imagery and remote sensing is preferred but not mandatory if strong ML background.

A good understanding of embedded systems from the perspective of deploying AI is required.

Experience or keen interest in deploying models in constrained environments is essential.

Soft Skills:

Ability to work independently in a remote-first setup.

Excellent communication skills to bridge technical and product conversations.

Curiosity, creativity, and a problem-solving mindset.